Backstepping-based adaptive dynamic programming for missile-target guidance systems with state and input constraints
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所属单位：自动化学院
发表刊物：JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
关键字：UNCERTAIN NONLINEAR-SYSTEMS BARRIER LYAPUNOV FUNCTIONS CONTINUOUS-TIME SYSTEMS OPTIMAL-CONTROL DESIGN STRICT-FEEDBACK FORM NEURAL-CONTROL ANGLE LAW SATURATION
摘要：In this paper, a novel backstepping-based adaptive dynamic programming (ADP) method is developed to solve the problem of intercepting a maneuver target in the presence of full-state and input constraints. To address state constraints, a barrier Lyapunov function is introduced to every backstepping procedure. An auxiliary design system is employed to compensate the input constraints. Then, an adaptive backstepping feedforward control strategy is designed, by which the tracking problem for strict-feedback systems can be reduced to an equivalence optimal regulation problem for affine nonlinear systems. Secondly, an adaptive optimal controller is developed by using ADP technique, in which a critic network is constructed to approximate the solution of the associated Hamilton-Jacobi-Bellman (HJB) equation. Therefore, the whole control scheme consists of an adaptive feedforward controller and an optimal feedback controller. By utilizing Lyapunov's direct method, all signals in the closed-loop system are guaranteed to be uniformly ultimately bounded (UUB). Finally, the effectiveness of the proposed strategy is demonstrated by using a simple nonlinear system and a nonlinear two-dimensional missile-target interception system. (c) 2018 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
ISSN号：0016-0032
是否译文：否
发表时间：2018-11-01
合写作者：Sun, Jingliang
通讯作者：刘春生